چکیده انگلیسی

This article presents a simulation study over a small supply chain, where the amount of work-in-process (WIP) is restricted. The supply chain consists of five linked machines, or production facilities, with stochastic operation times. A number of test cases are made where the number of jobs in the machines and the buffer areas are restricted. The restrictions are designed both in the Kanban way, linked to every machine, and in the CONWIP way, connected only to the total production line. But no Kanban-cards and -cells are involved in our study, just restricted inventories between the machines. With the same amount of limited WIP, CONWIP-control compared to Kanban-control presents a higher throughput rate, less time between jobs out, but the jobs stay on average longer in the system. The stochastic operation times cause that the upstream machine sometimes consumes the jobs in a rate that the downstream machine does not catch up with, therefore all available storage room temporarily are not used. Kanban- and CONWIP-control presents the same amount of average outflow per time unit with the same variation in operation times and with the same amount of real average WIP. But Kanban-control causes a lower utilisation of present available storage room and storage equipment than CONWIP. The user of Kanban and CONWIP can only control maximum WIP and not average WIP; average WIP is a consequence of existing variations, so the difference is important. The coefficient of variation of the lead-times increases when WIP increases; this is very difficult to handle in practical applications. Restricted WIP that shortens the lead-time and decreases its variation is more important than if it is a “push” or “pull” system. Finally, it is argued that CONWIP-control is to prefer over Kanban-control in theory, but in practice there is a lack of CONWIP installation guidelines.

مقدمه انگلیسی

Kanban is a technique for material and production control and performance. Originally presented as a Japanese technique Kanban was advocated for and spread by e.g. Monden (1983), Schonberger, 1982 and Schonberger, 1986), Shingo (1982), Sødahl (1984), etc. Similar techniques, two-bins, signal systems with numbered metal plates, etc., were used before in Nordic and western companies, not surprisingly because basically Kanban is a reorder point system but with a more visible reorder point. But the introduction of Kanban was a breakthrough for visible signal systems in western companies. The introduction of Kanban started a discussion of “pull” and “push” systems, where material requirements planning were considered as a push system and Kanban as a pull and just-in-time system.
When searching on the internet for pull and push systems the following definitions and categorisations of push versus pull can be found: push systems is said to mean “make all we can just in case”; and is said to be categorised by production approximation, anticipated usages, large lots, high inventories, waste, management by fire fighting, poor communication. Contrary pull systems is said to mean “Make what's needed when we need it” and categorised by production precision, actual consumption, small lots, low inventories, waste reduction, management by sight, better communication. The same thoughts and reasoning can be found elsewhere even in textbooks for management; the good things are pull and the bad things are push and causes and effects are not separated.
There exist many attempts tot define push and pull, cf. Pyke and Cohen (1990) and Bonney et al. (1999). For example, Spearman et al. (1990) mean that a pull system does not schedule the start of jobs but instead authorises production. Bonney et al. (1999) show that the definitions of push and pull are inconsistent between different researchers and arguments about performance are sometimes circular, if the performance of a pull system is poor then it may be suggested that this is because the fundamentals of just-in-time are not being observed, whereas, if the performance of a push system is poor, then that is a consequence of it being a push system.
Spearman et al. (1990) introduced a pull alternative to Kanban named CONWIP (CONstant Work In Process), where the work-in-process (WIP) is not constrained at every operation or machine instead the number of WIP in a total production “flow” is constrained. A production flow that may consists of several operations or machines and not just one machine.
For example, Hopp and Spearman, 1996 and Hopp and Spearman, 2000) and Silver et al. (1998) show the importance of restricted WIP. Too much (WIP) prolongs the time it take from start of production until it is ready to leave the production facility, to the next step in the supply chain or reach the end user. Too little WIP, when there are variations in production times and quantities, constrains the outflow by “starving” and “blocking” to a lower level then what would be the case with more WIP. (When there are a number of machines connected to a supply chain and no large enough buffers between the machines; a machine is starving when it cannot work because it has to wait for a job from the upstream machine and the machine is blocked when it cannot work with a new job because it cannot pass the finished job to the downstream machine, still working with its current job.)
Like Pyke and Cohen (1990) we mean it is not possible or useful to label a manufacturing system as being entirely push or pull. Most companies need both authorised and forecasted scheduled production; but very important the companies need restricted WIP. Push and pull are characteristics of the underlying decision-making process, which will contain elements of push or pull to varying degrees. To accomplish a short delivery time to the customers most companies must start production of components and semi-manufactured products according to forecasts often long before the customer order of the end product arrives. To achieve this material requirement planning (MRP) or reorder point systems (ROP) is mostly used in practical computer-based applications. Therefore, our interest also emanates from an alternative to MRP named cover-time planning (CTP) (cf. Segerstedt, 2006); CTP has similarities to CONWIP, WIP, in the machines and in stock for an item is constrained according to its current forecasted demand rate and expected lead-time. All these explain our interest in restricted WIP, Kanban and CONWIP and the reason we examine it in this simulation study. Despite the common attention to Kanban and CONWIP (Framinan et al. (2003) present a review, more recent publications e.g. Geraghty and Heavey (2004), Takahashi et al. (2005)), we have not found a similar study presenting similar results. Bonvik et al. (1997) also compare Kanban and CONWIP but in totally different way. The upcoming text has the following outlay. In Section 2, we present the test example and describe the simulation model. Thereafter, in Section 3, we present results from the simulations and its findings and finally some conclusions, discussions and extensions in Section 4.

نتیجه گیری انگلیسی

Our small experiments show the importance to keep track of WIP and not allow it to increase out of control. However, this is a not new finding; Nicolin (1959)1 explained that too much WIP would lead to future delays of customer orders. “Balance flow and not capacity” is an OPT-strategy (cf. Goldratt and Cox, 1984; Goldratt and Fox, 1986) that also implicates control of WIP. Hopp and Spearman (1996) and Silver et al. (1998) show that after WIP has reached a certain level more WIP does not increase the throughput rate it only prolongs the lead-time, which is also shown in our tests. Segerstedt (1999) suggests the obvious that orders should not be released at a higher rate than the rate of completion otherwise WIP continue to increase. Our test results show that an increase in WIP after a while does not improve the outflow rate much but it increases the variation (correlation of variation) in the lead-time time. Even for a relatively low variation in operation times when WIP increases the coefficient of variation for the lead-time, increases significantly, it seems to catch up and present almost the same coefficient of variation as for higher variations in the operation times (cf. Fig. 6). So, too much WIP not only prolongs the lead-time or throughput time it also increases its variation. This is in a practical application very difficult to handle; most plans cannot be followed, promises will not be fulfilled, etc. Both Kanban and CONWIP are hit by increased variation, our test results show no significant difference that one of them is less “hurt”. In practical applications, too little WIP is seldom the case, contrary too much WIP and long lead-times are mostly the case. This certainly explains the popularity and success of “pull systems”, their constrained WIP and decreased variations in WIP.
Our five machines can also be seen as five factories with inventories in between. Naturally, the capacity should be as balanced as possible among the different production facilities, and for an efficient supply chain the extra capacity for inventories should be placed in the end of the chain, so that the throughput rate can be as high as possible with as little as possible capital invested in average inventories.
The practical user of Kanban or CONWIP cannot explicitly control average WIP, it is a result of the circumstances, variations in operation times, etc.; the user can merely control maximum WIP. Therefore, we mean that CONstant in CONWIP should be exchanged to CONstrained. Regardless of Kanban-control or CONWIP-control the same “investment” in WIP, capital cost of tied up material in WIP presents the same throughput rate, time between jobs out or outflow per time unit and also the same lead-time, time in system. (Observations V and VI; this is deviating from the experiments in Muckstadt and Tayur, 1995a and Muckstadt and Tayur, 1995b.) However, Kanban needs more max WIP, therefore the fixed costs, or sunk costs, for Kanban is higher; more equipment for handling and storage is necessary and also more storage room; equipment and storage, which then has a lower utilisation than the corresponding for CONWIP. From that point of view we mean CONWIP-control is to prefer. Real Kanban-systems with Kanban-cells and -cards also require a lot of manual handlings; distribution of cards, changing of cards when demand changes. Little's formula “haunts” again; if we have to increase the throughput due to changed demand, we have to increase WIP or decrease lead-time. To decrease lead-time mostly requires a change in the production facility or system, more efficient machines, more working people. This is time consuming and often it is not easy to see and understand what to really do for improving the efficiency and shorten the lead-time. Therefore more WIP is the fast way to revise. When demand decreases, production also must decrease, and the opposite must be done, WIP should be decreased. This is a disadvantage for pure Kanban; the number of Kanbans must be changed, which explains why a Kanban installation prefers stable demand.
Hurley (1996) argues that placing buffers between each workstation is not the most effective mode of operation, placing the same amount of buffer stock in the shipping area and before the production constraint (s) produces superior results. Hurley at that time was probably not aware of the CONWIP concept but he suggests something like it and we notice our study support his ideas.
Left for future studies, extensions, are e.g. to study when one machine has less capacity than the others and when one machine has significantly higher variation in operation times than the others. The bottleneck should never be starved or blocked according to OPT theories; but other non-affected inventories may hardly be set to zero. Preliminary studies show that CONWIP-control solve this type of complication more or less automatically, and it could be suspected that it is very crucial how the restricted WIP is distributed among the different inventories using Kanban. If the suspicion can be verified by future studies; together with what is so far observed Kanban-control must be considered outperformed by CONWIP-control.
However, in a practical application it is not obvious how to install CONWIP. Which maximum WIP should be used? And in what way; item-wise (every route in the bill of material) or production facility wise (a part of the production area)? Most existing computerised Enterprise Resource Planning (ERP) systems do not contain facilities for CONWIP-control. Practical implications in literature how to use CONWIP exist, e.g. Golany et al. (1999), Hopp and Spearman (2000), Framinan et al. (2006), etc. But Kanban is more well known and well defined, it is described in most textbooks; it is just to follow the descriptions, visit a bench-marking installation, and apply it in parts of the production where the company has a high and fairly constant demand. Therefore an important extension for further studies is to examine and learn how CONWIP can easily be installed in different practical applications.